/podcast-transcript-fetcher

name: podcast-transcript-fetcher
description: Use when fetching, searching, or analyzing transcripts from Lenny's Podcast, Dwarkesh Podcast, Cheeky Pint, 20VC, or A16z Podcast. Tier 2 (RSS+Groq Whisper) is the recommended approach -- fast, free, and most reliable. Also use when asked to "get transcript", "find episode", "summarize podcast", or "search podcast content". Do not use for general web scraping or non-podcast audio transcription.
author: farizanjum
version: 1.1.0

Podcast Transcript Fetcher

Fetch transcripts from 5 supported podcasts. **Tier 2 (RSS+Groq Whisper) is the recommended approach** -- fast, free, and the most reliable across all podcasts. Tier 1 free sources are best-effort (limited availability). Tier 3 Taddy API is the premium/commercial option.

Quick Reference

# Get latest episode transcript (auto-detects best method)
python scripts/get_transcript.py "Lenny's Podcast" --latest

# Search by episode title or number
python scripts/get_transcript.py 20vc --episode "Marc Andreessen"
python scripts/get_transcript.py dwarkesh --episode 15

# Force specific method
python scripts/get_transcript.py "cheeky pint" --latest --method whisper
python scripts/get_transcript.py a16z --latest --method taddy

# Save to file
python scripts/get_transcript.py lennys --latest --output transcript.md

# List all supported podcasts
python scripts/get_transcript.py --list-podcasts

Supported Podcasts

| Podcast | Tier 1 (best-effort) | Tier 2 RSS+Whisper [RECOMMENDED] | Tier 3 Taddy (premium) | |---------|---------------------|-----------------------------------|------------------------| | Lenny's Podcast | GitHub archive (269 transcripts) | ✅ Substack RSS | ✅ Covered | | Dwarkesh Podcast | Website scrape + Substack PDF | ✅ Substack RSS | ✅ Covered | | Cheeky Pint | (none) | ✅ Transistor.fm RSS | ✅ Covered | | 20VC | Substack PDF | ✅ Libsyn RSS | ✅ Covered | | A16z Podcast | Website scrape | ✅ Simplecast RSS | ✅ Covered |

Implementation

1. Install Dependencies

# Core (always required)
pip install requests

# Cloud transcription (recommended — fast, free tier)
pip install groq
export GROQ_API_KEY="your-key"  # Get at https://console.groq.com

# Local transcription (free, needs ~5GB RAM)
pip install faster-whisper

# Audio compression (for Groq's 25 MB limit — Windows: winget/scoop)
#   winget install ffmpeg  or  scoop install ffmpeg

# Taddy API (commercial, optional)
export TADDY_API_KEY="your-key"  # Get at https://taddy.org

2. Get a Transcript

The script auto-selects the best method. **Tier 2 is the default recommendation:**

Tier 1 → Tier 2 (RECOMMENDED) → Tier 3
(best-effort)  (Whisper)  (Taddy API premium)

**Tier 1: Free direct sources (best-effort, limited availability)**

• Lenny's: Clones `ChatPRD/lennys-podcast-transcripts` and searches by title
• Dwarkesh: Substack PDF scrape
• 20VC: Substack PDF scrape
• A16z: Website scrape
• Cheeky Pint: No Tier 1 sources available
• Note: Tier 1 sources are best-effort and limited. Tier 2 (RSS+Whisper) is the recommended approach.

**Tier 2: RSS + Whisper transcription [RECOMMENDED]**

• Downloads MP3 from podcast RSS feed
• Compresses if >25 MB (ffmpeg)
• Transcribes via Groq Whisper API (free tier, ~10s per hour of audio)
• Fast, free, and works for every podcast in the registry
• Default recommendation for all use cases

**Tier 3: Taddy API (commercial/premium)**

• Requires `TADDY_API_KEY` ($75/mo+)
• Use for large-scale or production transcript needs
• Covers all 5 podcasts with auto-transcription

3. Analyze with AI

Once you have a transcript, pipe it to the agent for analysis:

I have this transcript from [podcast]. Can you:
1. Summarize the key arguments
2. Extract 3 actionable insights
3. Identify any controversial claims
4. Compare with [other podcast] on the same topic

Supported Workflows

Single Episode

| Scenario | Command | |----------|---------| | Latest episode | `get_transcript.py "Lenny's Podcast" --latest` | | Specific episode by title | `get_transcript.py 20vc --episode "Sam Altman"` | | Episode by number | `get_transcript.py dwarkesh --episode 42` | | Force Whisper transcription (Tier 2, recommended) | `get_transcript.py a16z --latest --method whisper` | | Force Taddy API (premium) | `get_transcript.py lennys --latest --method taddy` | | Save to Markdown | `get_transcript.py cheeky-pint --latest --output episode.md` | | JSON output | `get_transcript.py dwarkesh --latest --json` |

Cross-Podcast Search & Batch

| Scenario | Command | |----------|---------| | Search all podcasts by keyword | `get_transcript.py --search "Marc Andreessen"` | | Search by guest name | `get_transcript.py --guest "Sam Altman"` | | Search within one podcast | `get_transcript.py "Lenny's Podcast" --search "vibe coding"` | | Batch-transcribe last N episodes | `get_transcript.py "Dwarkesh Podcast" --last 5` | | Search + transcribe top matches | `get_transcript.py --search "AI safety" --transcribe` | | Pipeline with custom count | `get_transcript.py --search "scaling laws" --transcribe --transcribe-count 5` | | Filtered search pipeline | `get_transcript.py "A16z Podcast" --search "crypto" --transcribe` |

Output Structure

Batch transcription saves to `output/` with per-podcast subdirectories:

output/dwarkesh-podcast/Dwarkesh Podcast_2024-01-15_agi-is-still-30-years-away.md
output/20vc/20 Minutes VC (20VC)_2024-03-10_funding-round-analysis.md

Each file includes a YAML frontmatter header:

---
podcast: Dwarkesh Podcast
episode: AGI is still 30 years away
date: 2024-01-15
url: https://...
source: whisper
---

Podcast Registry

The registry at `scripts/podcasts.json` maps each podcast to its RSS feeds, transcript sources, and API endpoints. To add new podcasts:

{
  "id": "new-podcast",
  "name": "New Podcast",
  "rss": "https://example.com/feed.xml",
  "transcript_sources": {
    "primary": {"type": "website_scrape", "url":